About Lodestar
Lodestar's mission is to develop the first "Protect and Defend" capability for high-value space assets in orbit. Our flagship product _MITHRIL_ is our hardware-agnostic, AI-enabled autonomy software suite that enables us to augment any off-the-shelf spacecraft with the ability to autonomously detect, characterise, and reversibly neutralise orbital threats. By building on the proven space heritage of our best-in-class satellite-bus partners and fully integrating _MITHRIL_ into single unified platform, we deliver an end-to-end, autonomous in-space bodyguarding service.
About the Job
At Lodestar, as a Graduate Software Engineer (I or II): State Estimation & Prediction, you’ll be leading the development of our state estimation and prediction models at the core of Lodestar’s flagship product, _MITHRIL_. You’ll be focusing on researching and developing algorithms that fuse probabilistic estimation with machine learning to track targets, predict trajectories and assess intent.
We proudly have an "extreme ownership" oriented engineering culture.
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What You’ll Do
* Contribute to the design and implementation of Lodestar's core state estimation and prediction architecture for autonomous spacecraft operations
* Support research into novel estimation and prediction algorithms, from literature review through training and tuning to optimisation and deployment
* Implement, test, and benchmark classical and neural estimators that track the current state and trajectory of multiple dynamic targets in real time
* Build and evaluate neural models that forecast future trajectories and behavioural patterns of targets
* Assist in the development of intent inference models that identify actions and dynamically rank threat levels
* Integrate state estimation and prediction models into mission simulation environments and autonomy decision systems
* Collaborate with cross-functional teams, including perception and on-board autonomy, to ensure prediction fidelity, robustness, and scalability across missions
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Basic Qualifications
* Bachelor's, Master's, or PhD in Computer Science, Aerospace, Robotics, Applied Mathematics, or a related field, completed within the last 24 months or due to be completed before your start date
* Working proficiency in C++ and Python, evidenced through coursework, research, internships, or personal projects
* Grounding in probabilistic state estimation (Kalman filters, particle filters, Bayesian inference), whether from taught modules, research, or self-directed work
* Practical exposure to a deep learning framework (PyTorch, TensorFlow), including sequence modelling (seq2seq, RNNs, LSTMs, Transformers)
* Familiarity with trajectory modelling, multi-body dynamics, or orbital mechanics
* Demonstrated ability to work through open-ended technical problems and communicate your reasoning clearly
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Preferred Skills & Experience
* Internship, industrial placement, or research assistantship in aerospace, robotics, estimation, or a related field
* A dissertation, thesis, or capstone project in state estimation, sensor fusion, or trajectory forecasting
* Experience applying sequence-to-sequence models to forecasting problems in dynamic environments
* Familiarity with sensor fusion techniques (e.g. combining radar, optical, and inertial data)
* Exposure to GPU acceleration (CUDA, TensorRT) for neural network training and inference
* Experience with Linux, Git, and CI/CD pipelines
* Familiarity with containerisation tools such as Docker and Kubernetes
* Awareness of real-time systems, multi-threading, and performance optimisation
* Understanding of networking and communication protocols for distributed autonomy systems
* Contributions to open-source projects, or participation in student rocketry, CubeSat, robotics, or autonomous vehicle teams
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ITAR Requirements
_To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here._
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Compensation & Benefits
* Our full band structure for this role:
* (P1) Entry: $99,000 - $133,000 / year
* (P2) Developing: $115,000 - $174,000 / year
* Meaningful equity incentives as part of our employee option pool
* Flexible PTO with generous paid vacation, holidays, and sick leave
* Comprehensive medical, dental & vision coverage
* 401(k) retirement plan with company match
* Based in Los Angeles
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Additional Information
_Compensation bands are determined by role, level, location, and alignment with market data. Individual level and base pay is determined on a case-by-case basis and may vary based on job-related skills, education, experience, technical capabilities and internal equity. In addition to base salary, for full-time hires, you may also be eligible for long-term incentives, in the form of stock options , and access to medical, vision and dental coverage, as well as access to a 401(k) retirement plan._
_Lodestar is an Equal Opportunity Employer; employment with Lodestar is governed on the basis of merit, competence and qualifications and will not be influenced in any manner by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability or any other legally protected status._